Research on Change in Relationship of American Biotechnology Industry and Pharmaceuticals Industry Due to Covid-19
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Purpose: This paper examines the causal and cointegrating relationship between economic growth and CO2 emissions in a multivariate framework by including imports and exports as others control variables for an emerging economy like Bangladesh. Design/methodology: The paper applied vector error correction model (VECM) Granger casualty test for assessing the direction of causality and variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the explanatory variables over time. LB (Q-stat) test is to determine data properties and WILD test is to assess short run causality from independent variables to dependent variable. Findings: The study results revealed that variables are integrated in the same order. The results of Johansen Juselius cointegration tests indicate that there is a unique long-term or equilibrium relationship among variables. Again, Granger causality test revealed that short run unidirectional causality are running from carbon dioxide emission to exports, GDP to import, and from import to carbon dioxide emissions. Variance decomposition function shows that the positive shocks in error term will produce positive effects on all variables in the long run. Therefore, a concerted effort from all national and international stakeholders, i.e., enterprises, consumers, and governments are expected to take measures to offset carbon emission and pursue environment-friendly trade plan for better managing the cities and regions in order to fight against global warming and climate change risk.
Johansen test
Vector autoregression
Causality
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Chemical industry
Pharmaceutical Manufacturing
Pharmaceutical Sciences
Drug industry
Pharmaceutical drug
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Variance-based sensitivity analysis
Representation
Realized variance
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The paper studies empirically the impact of trade and on GDP in Henan Province,by using time series data of exports amout and GDP from 1993 to 2009 and based on JJ cointegration test,impulse response function and variance decomposition.The study results show that: there is a long-term and stable equilibrium relationship and significant causality existing between export trade and GDP as well as FDI and GDP ;the trade and have a strong effect on improving the economic growth of Henan Province,and their impulse response to economic growth is generally positive response,while plays a more important improving role on economic growth than FDI.Finally,the paper gives suggestions about improving export、and to improve economic growth based on study results.
Impulse response
Export trade
Johansen test
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The paper questions the reasonability of using forecast error variance decompositions for assessing the role of different structural shocks in business cycle fluctuations. It is shown that the forecast error variance decomposition is related to a dubious definition of the business cycle. A historical variance decomposition approach is proposed to overcome the problems related to the forecast error variance decomposition.
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This paper develops a multi-way analysis of variance for non-Gaussian multivariate distributions and provides a practical simulation algorithm to estimate the corresponding components of variance. It specifically addresses variance in Bayesian predictive distributions, showing that it may be decomposed into the sum of extrinsic variance, arising from posterior uncertainty about parameters, and intrinsic variance, which would exist even if parameters were known. Depending on the application at hand, further decomposition of extrinsic or intrinsic variance (or both) may be useful. The paper shows how to produce simulation-consistent estimates of all of these components, and the method demands little additional effort or computing time beyond that already invested in the posterior simulator. It illustrates the methods using a dynamic stochastic general equilibrium model of the US economy, both before and during the global financial crisis.
Variance-based sensitivity analysis
Realized variance
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The paper studies empirically the impact of trade, to GDP in Henan province, by using time series data of exports, and GDP from 1993 to 2009 and based on JJ cointegration test, impulse response function and variance decomposition. The study results show that: there is long-term and stable equilibrium relationship and significant causality existing between export trade and GDP as well as FDI and GDP ; Export trade, has the effect for improving economic growth of Henan, their impulse response to economic growth is generally positive response. But plays a more important improving role to economic growth than FDI. Finally, the paper gives suggestions about improving export、FDI in order to improve economic growth based on study results.
Impulse response
Vector autoregression
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Abstract This paper develops a multiway analysis of variance for non-Gaussian multivariate distributions and provides a practical simulation algorithm to estimate the corresponding components of variance. It specifically addresses variance in Bayesian predictive distributions, showing that it may be decomposed into the sum of extrinsic variance, arising from posterior uncertainty about parameters, and intrinsic variance, which would exist even if parameters were known. Depending on the application at hand, further decomposition of extrinsic or intrinsic variance (or both) may be useful. The paper shows how to produce simulation-consistent estimates of all of these components, and the method demands little additional effort or computing time beyond that already invested in the posterior simulator. It illustrates the methods using a dynamic stochastic general equilibrium model of the US economy, both before and during the global financial crisis. Keywords: Extrinsic varianceInformationIntrinsic variancePredictionSimulationJEL Classification: C53C1 ACKNOWLEDGMENTS The first author, support from Australian Research Council grant 110104732 is gratefully acknowledged. The views expressed do not represent those of the ECB.
Variance-based sensitivity analysis
Realized variance
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Abstract In this paper, we propose a new method called the total variance method and algorithms to compute and analyse variance decomposition for nonlinear economic models. We provide theoretical and empirical examples to compare our method with the only existing method called generalized forecast error variance decomposition (GFEVD). We find that the results from the two methods are different when shocks are multiplicative or interacted in nonlinear models. We recommend that when working with nonlinear models researchers should use the total variance method in order to see the importance of indirect variance contributions and to quantify correctly the relative variance contribution of each structural shock.
Variance-based sensitivity analysis
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